Re: st: maximum likelihood procedures for oprobit

[Richard Williams <Richard.A.Williams.5@ND.edu>]

At 11:04 PM 12/7/2005, Sunhwa Lee wrote:
> Thanks a lot for the quick reply.
> -- I tried that code myself to find the same error message.
> -- I am using Ver.8
> -- oprobit is attached this time with -ml-.
>
> Here is attached again the right code that has just been tested okay.
I think it is a problem with the data more than the program.  This 
simpler model works fine.  Note that the testparm command after 
oprobit gives you a Wald chi-square, which you can then compare with 
the results from your program.

. oprobit rep mpg foreign

Iteration 0:   log likelihood = -97.440603
Iteration 1:   log likelihood = -82.871392
Iteration 2:   log likelihood = -82.681234
Iteration 3:   log likelihood = -82.680255
Iteration 4:   log likelihood = -82.680255

Ordered probit regression                         Number of obs   =         74
                                                  LR chi2(2)      =      29.52
                                                  Prob > chi2     =     0.0000
Log likelihood = -82.680255                       Pseudo R2       =     0.1515

------------------------------------------------------------------------------
       rep78 |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         mpg |   .0445906   .0255612     1.74   0.081    -.0055083    .0946896
     foreign |    1.37699   .3275072     4.20   0.000     .7350882    2.018893
-------------+----------------------------------------------------------------
       /cut1 |   .2926372   .5296403                     -.7454387    1.330713
       /cut2 |   1.631237   .5418085                      .5693114    2.693162
       /cut3 |   2.731538    .607935                      1.540007    3.923069
------------------------------------------------------------------------------

. testparm *

 ( 1)  [rep78]mpg = 0
 ( 2)  [rep78]foreign = 0

           chi2(  2) =   26.87
         Prob > chi2 =    0.0000

. ml model lf myoprobit (rep =mpg foreign, nocons)(tau1: ) (tau2:) (tau3:),
.
. ml maximize

initial:       log likelihood =     -<inf>  (could not be evaluated)
feasible:      log likelihood = -4165.2347
rescale:       log likelihood = -162.36841
rescale eq:    log likelihood = -98.148979
Iteration 0:   log likelihood = -98.148979
Iteration 1:   log likelihood = -83.137823
Iteration 2:   log likelihood = -82.682056
Iteration 3:   log likelihood = -82.680255
Iteration 4:   log likelihood = -82.680255

                                                  Number of obs   =         74
                                                  Wald chi2(2)    =      26.87
Log likelihood = -82.680255                       Prob > chi2     =     0.0000

------------------------------------------------------------------------------
       rep78 |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
eq1          |
         mpg |   .0445907   .0255612     1.74   0.081    -.0055083    .0946896
     foreign |    1.37699   .3275072     4.20   0.000     .7350882    2.018893
-------------+----------------------------------------------------------------
tau1         |
       _cons |   .2926377   .5296404     0.55   0.581    -.7454384    1.330714
-------------+----------------------------------------------------------------
tau2         |
       _cons |   1.631237   .5418086     3.01   0.003     .5693117    2.693163
-------------+----------------------------------------------------------------
tau3         |
       _cons |   2.731539   .6079352     4.49   0.000     1.540008     3.92307
------------------------------------------------------------------------------



-------------------------------------------
Richard Williams, Notre Dame Dept of Sociology
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